The FRISK® Score Examined: Part 1 - The Wisdom of the Markets
When it comes to predicting public company stress, several metrics can be used to illuminate the signs of financial stress that payment trends cannot foresee. Since the FRISK® score leverages the information provided by four key metrics – stock market capitalization and volatility, financial ratios, bond agency ratings and crowdsourced CreditRiskMonitor subscriber usage data – it is able to predict public company risk with 96% accuracy.
The magic is in the blend: these four inputs balance each other out brilliantly when placed within a formula together. Finding that recipe took a decade of research, as the structural statistical model used for the FRISK® score was developed and back-tested using company data and bankruptcies between 2003 and 2013 - a period of covering 9,600 unique businesses and 580 bankruptcies, with the Great Recession arriving in 2007. The score is also unique in the commercial credit space because it does not use payment data, which our research shows to be misleading for predicting public company bankruptcy.
In this series, we explore each of these vital inputs in detail, dissecting their usefulness, strengths and weaknesses.
Stock Market Capitalization and Volatility: The Merton Model
Stock market data is included in the FRISK® score through the capturing of a company's stock market capitalization, dividend information and stock volatility. The inclusion of this factor incorporates the wisdom of markets into CreditRiskMonitor's proprietary FRISK® score, updating the score daily with the market’s view of the financial risk of a particular company.
There is a common sense reason why there should be a relationship between a company’s financial risk and its stock market performance: Stockholders have the lowest seniority in recovering their investment in the event a company is dissolved. Thus, they are very sensitive to the risk of insolvency for a company. The market's current sentiment is quickly reflected in the price action of a company's stock.
The Pros and Cons
In the 1970’s, Prof. Robert C. Merton of the Massachusetts Institute of Technology (MIT) wrote a seminal academic paper in the field of finance, in which he explained that stock market data can provide information as to the financial risk of a company. This is consistent with the efficient market hypothesis, which says that all benefits and risks about a stock are reflected in its stock price and its volatility.
While this hypothesis is not strictly true, and some of the related drawbacks of this approach are discussed below, over the course of the past three-plus decades, the Merton Model method (and its variations) has proven to be a useful tool in predicting default and bankruptcy. The Merton Model is supported by a large body of published academic research.
The significant benefit of the Merton approach is that it provides financial risk information on a daily basis. This information is based on the change in share prices of companies as a result of their trading on stock exchanges. There's no need to wait up to three months for the next quarterly financial statements to come out.
One of the drawbacks of the Merton approach, however, is that stock performance is not only influenced by the market’s view of a particular company, but also by the behavior of the market or industry as a whole. In addition, the stock market sometimes overreacts to news about particular companies. For both of these reasons, the Merton Model’s estimate of a company’s financial risk will itself be more volatile than the other methods of estimating financial risk.
The volatility of the Merton Model makes this metric alone less efficient in predicting bankruptcy, which is why the FRISK® score offsets the model with more stable metrics like financial ratios and bond ratings. These more steady components add balance to the FRISK® score’s model.
Creating a Sense of Balance
Over the short term, the stock market is a “voting machine and not a weighing machine,” as the father of fundamental analysis, Benjamin Graham, would say. This creates both a benefit and a problem for the FRISK® score: Although including the wisdom of markets in the score can highlight emotionally led signals, it allows the FRISK® Score to be highly reactive to events that are taking place in real-time.
It is one of the key reasons why the FRISK® score has achieved such impressive success in predicting public company financial risk. The real value, however, is in including this factor together with financial ratios, bond agency ratings and crowd-sourced CreditRiskMonitor subscriber usage data, creating a more robust picture of risk. In the second article in this five-part series, we'll delve into financial ratios, including the Altman Z” score.
CreditRiskMonitor is a financial news and analysis service designed to help professionals stay ahead of public company risk quickly, accurately and cost-effectively. More than 35% of the Fortune 1000, plus thousands more worldwide, rely on our commercial credit reporting and predictive risk analytics for assessing the financial stability of over 58,000 global public companies.
At the core of CreditRiskMonitor’s service is its 96% accurate FRISK® score, which is formulated to predict public company bankruptcy risk. One of four key components calculated in the FRISK® score is crowdsourced subscriber activity. This unique system tracks subscribers' patterns of research activity, capturing and aggregating the real-time concerns of what are essentially the key gatekeepers of corporate credit. Other features of CreditRiskMonitor’s service include timely news alerts, the Altman Z” score, agency ratings, financial ratios and trends. CreditRiskMonitor’s network of trade contributors provides more than $135 billion in trade data on their counterparties every month, giving them visibility into their biggest dollar risks.